JP2022107626A - System and method for improving visualization of traffic state - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide traffic state information.

SOLUTION: A method to be executed in a computer for determining a traffic state includes a step of acquiring traffic sample data to be associated with a first direction of traffic on a first road segment. The traffic sample data includes data which indicates a plurality of movement speeds to be associated with a plurality of objects. The method includes: a step of determining a plurality of average traffic speeds with respect to the first direction of the traffic on the first road segment at least partially based on the movement speeds; a step of associating each one of the average traffic speeds with at least one of a plurality of traffic types; a step of determining map data at least partially based on the average traffic speeds to be associated with the traffic types; and a step of transmitting the map data corresponding to at least one of the traffic types to a client device in response to a request.

SELECTED DRAWING: Figure 5

COPYRIGHT: (C)2022,JPO&INPIT

Description

TECHNICAL FIELD This disclosure relates generally to providing traffic condition information.

A Geographic Information System (GIS) is a system for storing, retrieving, and manipulating data that is stored and indexed according to the geographic coordinates of elements of the data. The system is generally capable of utilizing various data types such as images, maps and tables. GIS technology can be integrated into Internet-based map applications.

Such a map application may be, or may be otherwise associated with, a software application that displays an interactive digital map. For example, map applications may run on laptop and tablet computers, mobile phones, car navigation systems, portable global positioning system (GPS) units, and the like.

In general, map applications can display various types of geographic data, including terrain data, street data, city transit information, and traffic data. Additionally, the geographic data may be graphical or based on photographs such as satellite imagery. Still further, map applications can display information in two-dimensional (2D) or three-dimensional (3D) formats.

Traffic condition information can be visualized by displaying different colors depending on the speed of the cars on the road. However, this can be misleading in some cases.

Aspects and advantages of the disclosure are set forth in part in the description that follows, or may be learned from the description, or may be learned through practice of the embodiments.

This specification generally describes methods and systems for providing improved traffic information by providing traffic type-specific traffic information. Different types of traffic may move at different speeds. For example, certain vehicles may have higher speed lanes such as high occupancy toll lanes or express toll lanes with more than a specified number of passengers, or certain vehicle types (trucks or buses, etc.). Determining the average traffic speed on a route without considering such lanes is likely to result in an inaccurate average traffic speed. Additionally, providing the wrong type of traffic information to a particular user or vehicle type is likely to result in an inaccurate representation of traffic conditions. In view of the above, the methods and systems described herein provide a means for calculating traffic speeds for different traffic types and a means for providing the correct type of traffic information in response to a request for traffic information. provide the means.

One exemplary aspect of the present disclosure is directed to a computer-implemented method for determining traffic conditions. The method includes obtaining traffic sample data associated with a first direction of traffic on a first road segment, the traffic sample data including data indicative of a plurality of travel speeds associated with a plurality of objects. The method includes determining a plurality of average traffic speeds for a first direction of traffic on the first road segment based at least in part on the plurality of travel speeds. The method includes associating each of a plurality of average traffic speeds with at least one of a plurality of traffic types. The method includes determining map data based at least in part on a plurality of traffic types and associated average traffic speeds. The method includes transmitting map data corresponding to at least one of a plurality of traffic types to the client device in response to the request.

Another exemplary aspect of the present disclosure is directed to a computer-implemented method for determining traffic conditions. The method includes receiving one or more requests for traffic condition information from a user, the one or more requests including data indicative of a first location, a second location, and a traffic type. The method includes determining a first transit route from a first location to a second location, the first transit route being one or more associated with a first traffic type from a plurality of traffic types. Contains multiple transit areas. The method includes determining map data indicative of a first transit duration for the first transit route, the first transit duration corresponding to a traffic speed associated with the first traffic type. The method includes providing map data to a user in response to a request for traffic condition information.

Another example aspect of the disclosure is directed to a computing system. A computing system includes one or more processors and one or more tangible, non-transitory computer-readable media, collectively referred to as a computing system when executed by the one or more processors. store instructions that cause the to perform an action. The operations include receiving one or more requests for transit information from a user, the one or more requests including data from the user indicating a first location, a second location, and a traffic type. . The operation includes determining a first transit route from a first location to a second location, the first transit route being one or more traffic types associated with a first traffic type from a plurality of traffic types. Contains multiple transit areas. The operation includes identifying a first transit area from one or more transit areas, the first transit area being associated with two or more traffic types from the plurality of traffic types and two or more traffic types. A traffic type includes a first traffic type and a second traffic type from a plurality of traffic types. The operation includes determining a first transit duration and a second transit duration for the first transit route, the first transit duration corresponding to a traffic speed associated with the first traffic type. , the second transit time corresponds to the traffic speed associated with the second traffic type. The operation determines the first traffic type or the second traffic type with the user based at least in part on the first transit duration, the second transit duration, and data indicative of the traffic type received from the user. Including the step of associating. Operations include providing map data to a user in response to a request for transit information, the map data corresponding to a traffic type associated with the user.

Another exemplary aspect of the present disclosure is directed to a computer-implemented method for determining traffic conditions. The method includes receiving, by one or more computing devices, a request for traffic condition information from a user, the request including data indicative of a first location, a second location, and a first traffic type. include. The method includes determining, by one or more computing devices, one or more transit routes from a first location to a second location, each transit route being associated with a first traffic type. contains one or more road segments The method includes determining, by one or more computing devices, traffic condition information associated with traffic corresponding to the first traffic type for each of the one or more transit routes. The method generates, by one or more computing devices, map data indicative of traffic condition information associated with traffic corresponding to a first traffic type for at least one of the one or more transit routes. including the step of determining. The method includes providing, by one or more computing devices, map data to a user in response to a request for traffic condition information.

Another exemplary aspect of the present disclosure is directed to a computer-implemented method for determining traffic conditions. The method includes receiving, by one or more computing devices, a request for traffic condition information from a user, the request including data indicative of one or more road segments. The method includes obtaining, by one or more computing devices, at least one of user data or vehicle data indicative of a traffic type associated with a request for traffic condition information. The method includes determining, by one or more computing devices, map data including traffic condition information associated with traffic corresponding to the traffic type for one or more road segments. The map data is determined based at least in part on user data or vehicle data indicating a traffic type associated with the request for traffic condition information. The method includes providing, by one or more computing devices, map data to a user in response to a request for traffic condition information.

Other exemplary aspects of this disclosure are directed to systems, methods, vehicles, apparatus, tangible non-transitory computer-readable media, and memory devices for determining traffic conditions.

These and other features, aspects, and advantages of various embodiments become better understood with reference to the following description and appended claims. The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the disclosure and, together with the description, serve to explain the principles involved.

A detailed discussion of embodiments directed to those skilled in the art is set forth herein and the specification refers to the accompanying drawings.

1 depicts an example computing environment, according to an example embodiment of the present disclosure; FIG. FIG. 4 illustrates an example event sequence, according to an example embodiment of the present disclosure; FIG. 4 illustrates an example event sequence, according to an example embodiment of the present disclosure; FIG. 4 illustrates an example event sequence, according to an example embodiment of the present disclosure; FIG. 4 illustrates an example event sequence, according to an example embodiment of the present disclosure; FIG. 3 illustrates visualization of traffic condition information, according to an exemplary embodiment of the present disclosure; FIG. 3 illustrates visualization of traffic condition information, according to an exemplary embodiment of the present disclosure; FIG. 3 illustrates visualization of traffic condition information, according to an exemplary embodiment of the present disclosure; FIG. 4 illustrates an example distribution of travel speeds on a road segment, according to an example embodiment of the present disclosure; FIG. 4 illustrates an example distribution of travel speeds on a road segment, according to an example embodiment of the present disclosure; 4 is a flow diagram for determining traffic condition information, according to an exemplary embodiment of the present disclosure; 4 is a flow diagram for associating multiple traffic speeds with traffic types, according to an exemplary embodiment of the present disclosure; 4 is a flow diagram for determining traffic condition information, according to an exemplary embodiment of the present disclosure; 4 is a flow diagram for determining traffic condition information, according to an exemplary embodiment of the present disclosure; 4 is a flow diagram for displaying traffic condition information, according to an exemplary embodiment of the present disclosure;

Reference numbers that are repeated across multiple figures are intended to identify the same component or feature in different implementations.

Exemplary aspects of this disclosure are directed to methods and systems for determining traffic condition information. Specifically, the geographic information service provides traffic samples that show traffic (e.g., vehicle traffic, bicycle traffic, pedestrian traffic, etc.) associated with multiple objects (e.g., automobiles, bicycles, pedestrians, etc.) within a transit area. Data can be obtained. The geographic information service can determine one or more average traffic speeds associated with the transit area (e.g., one or more average traffic speeds of traffic within the transit area) based on the traffic sample data, and the geographic The information service may associate each average traffic speed with at least one of a plurality of traffic types. Multiple traffic types are, for example, normal traffic, high-speed traffic (e.g., over-crowded vehicle (HOV) traffic, toll-lane traffic), and certain types of vehicles (e.g., using a certain traffic lane). transportation (trucks or buses) for which transportation may be required. The geographic information service can determine traffic condition information for transit areas based on multiple traffic types and associated average traffic speeds. In response to a request for traffic condition information, the geographic information service determines map data indicative of traffic condition information and transmits map data corresponding to at least one of a plurality of traffic types to the requesting entity. can do.

According to aspects of the present disclosure, the traffic condition information includes, for example, data indicative of one or more traffic speeds associated with traffic corresponding to one or more traffic types within the transit area; It may include transit duration and/or other information associated with movement in the transit area.

In some implementations, a transit area may include one or more road segments. Each road segment may include one or more traffic lanes, each traffic lane indicating a traffic type (e.g., normal traffic, express traffic, certain types of vehicle traffic, etc.), traffic direction, and/or traffic. Or it may be associated with a reference traffic speed (eg, speed limit). Traffic sample data may include speed and direction of traffic on road segments. In some implementations, traffic sample data may include traffic lanes and/or traffic types associated with traffic on road segments. The traffic condition information may include one or more traffic speeds (eg, average traffic speed) of traffic on the road segment in each of one or more directions of traffic associated with the road segment. Traffic condition information is one or more transit times for traffic on a road segment (for example, the time it takes to travel from a first end of a road segment to a second end of a road segment based on traffic speed) can also include

In some implementations, the transit path from the first location to the second location may include one or more transit regions. Traffic condition information may include one or more traffic speeds (eg, one or more average traffic speeds) of traffic on each road segment of one or more transit regions in the transit route. One or more traffic speeds may each be associated with traffic corresponding to different traffic types. Traffic condition information may also include one or more transit times (eg, the time it takes to travel from a first end to a second end) for traffic on each road segment. One or more transit times may each be associated with traffic corresponding to different traffic types. In some implementations, the traffic condition information includes one or more traffic speeds for the entire transit route (e.g., for traffic corresponding to one or more different traffic types, each weighted by the distance associated with the road segment). average traffic speed of traffic on a road segment) and/or one or more transit durations for the entire transit route (e.g., for traffic corresponding to one or more different traffic types, the time it takes to move from one position to a second position).

In some implementations, the traffic condition information may include identifiers such as numbers for one or more traffic speeds. Alternatively, the traffic condition information may include identifiers (eg, color-coded identifiers) corresponding to predetermined ranges of traffic speeds. The identifier can be used in connection with a graphical user interface (GUI) for providing traffic condition information to users. For example, a GUI may include a map of multiple road segments displayed based on color-coded identifiers associated with each road segment. Each road segment in the map may be displayed with a color, shading, or other visual characteristic corresponding to the color-coded identifier associated with the road segment. The use of color-coded identifiers is given only as an example. It will be appreciated that any type of visual, audible, or other identifier may be provided in connection with the graphical user interface to distinguish traffic speeds.

As an example, if the traffic speed for the road segment exceeds the speed limit for the transit area by at least a first threshold amount, then the traffic condition information is a first identifier (e.g., "green") associated with the road segment. a color-coded identifier that is If the traffic speed for the road segment equals the speed limit or exceeds the speed limit by an amount less than the first threshold amount, the traffic condition information is a second identifier associated with the road segment (e.g., " a color-coded identifier that is "yellow"). If the traffic speed for the road segment is less than the speed limit for the road segment, the traffic condition information may include a third color-coded identifier (eg, a color-coded identifier that is "red") associated with the road segment.

As another example, if the traffic speed for the road segment is below the speed limit for the road segment by at least a first threshold amount, then the traffic condition information is a first identifier associated with the road segment (e.g., "red ”). A second identifier (e.g., a color-coded identifier that is "yellow") associated with the road segment if the traffic speed for the road segment is below the speed limit for the road segment by an amount less than the first threshold amount. can include The traffic condition information may include a third identifier (eg, a color-coded identifier that is "green") associated with the road segment if the traffic speed for the road segment is equal to or greater than the speed limit for the road segment.

As another example, if the average traffic speed on a road segment is 50 mph, traffic condition information may include data indicating 50 mph for the road segment. Alternatively, if the average traffic speed of normal traffic on the road segment is 40 mph, and the average speed of fast traffic on the road segment is 60 mph, then the traffic condition information is for normal traffic on the road segment. Data indicating 40 mph corresponding and/or data indicating 60 mph corresponding to high speed traffic on the road segment may be included.

As another example, consider an average traffic speed for a road segment of 50 mph, a speed limit associated with the road segment of 40 mph, and a first threshold of 5 mph. In this example, the traffic speed for the road segment exceeds the speed limit by a first threshold amount of at least 5 mph. Thus, the traffic condition information may include "green" color-coded identifiers for the road segments. Alternatively, if the speed limit associated with the road segment is 45 mph and the first threshold is 10 mph, the traffic speed for the road segment exceeds the speed limit by an amount less than the first threshold amount of 10 mph. and the traffic condition information may include a "yellow" color-coded identifier for the road segment. Alternatively, if the speed limit associated with the road segment is 55 mph, the traffic speed for the road segment is below the speed limit and the traffic condition information may include a "red" color coded identifier.

According to example embodiments, an application programming interface (API) may be provided. For example, an API may be used by a server as part of a geographic information service to allow one or more applications running on a client computing system to interface with the server and exchange data associated with traffic. may be provided by a computing system. A server-computing system may include one or more computing devices (eg, computers, servers, mainframes, virtual computing platforms, etc.). A client computing system is one or more computing devices (e.g., computers (e.g., desktop computers, laptop computers, etc.), mobile computing devices (e.g., tablet computers), associated with a common (or same) user. , smart phones, etc.), wearable computing devices (eg, smart watches, etc.), vehicle computing devices (eg, vehicle computing systems, navigation systems, etc.). In some examples, an API is used by a client as part of a geographic information service to allow one or more applications running on the client computing system to exchange data with a server computing system. provided in a computing system. In some implementations, a single computing system may include a server computing system and a client computing system. In some implementations, the client computing system can utilize an API to communicate with the server computing system to obtain traffic condition information for the transit area. For example, the API may receive a call from one of the applications requesting traffic condition information for one or more transit areas (eg, one or more road segments). In response to calls received through the API, the server computing system can return traffic condition information through the API to the requesting application.

According to aspects of this disclosure, an API call to request traffic condition information for a transit area may include, for example, data indicative of the transit area (eg, an identifier corresponding to the transit area). In some implementations, the API may receive API calls from applications requesting traffic condition information for one or more road segments (e.g., an API call may may include one or more identifiers corresponding to the segment). In some implementations, the API may receive an API call from an application requesting traffic condition information about a transit route between a first location and a second location. In some implementations, an API call may include a traffic type (eg, normal traffic, express traffic, specific types of vehicle traffic, etc.).

As an example, in response to an API call containing data indicative of one or more road segments, the geographic information service may, for example, associate one or more traffic speeds (e.g., direction of traffic) with traffic on the road segments. (e.g., via the server computing system) can determine traffic condition information for the road segment, such as one or more average traffic speeds), and/or transit times for traffic on the road segment. . Each of the one or more traffic speeds may be associated with traffic corresponding to a different traffic type. Geographic services can return traffic information to requesting applications via APIs.

As another example, in response to an API call containing data indicating one or more road segments and a traffic type, the geographic information service may, for example, determine traffic speeds associated with traffic corresponding to the traffic type, and/or traffic Traffic condition information for road segments based on traffic type, such as transit times associated with traffic corresponding to the type, can be determined (eg, via a server computing system). The geographic information service may determine transit times associated with traffic corresponding to a traffic type for a road segment based on, for example, traffic speeds associated with traffic corresponding to the traffic type and distances associated with the road segment. . The geographic information service can return traffic condition information to the requesting application.

As another example, in response to an API call containing data indicating a first location and a second location, the geographic information service generates one or more transit routes from the first location to the second location. It can be determined (eg, via a server computing system). A transit route may include one or more road segments between the first location and the second location. In some implementations, two or more transit paths may each include one or more road segments in common. The geographic information service may, for example, provide transit information, such as one or more traffic speeds of traffic on a road segment, and/or one or more transit times for traffic on a road segment, as described above. Traffic condition information can be determined for road segments in the route. Additionally or alternatively, the traffic condition information may include one or more traffic speeds for the entire transit route and/or one or more travel times for the entire transit route, as described above. The geographic information service can return traffic condition information to the requesting application.

As another example, in response to an API call that includes a first location, data indicating a second location, and data indicating a traffic type, the geographic information service sends a one-way traffic from the first location to the second location. One or more transit paths can be determined (eg, via a server computing system). A transit route may include one or more road segments between the first location and the second location. In some implementations, two or more transit paths may each include one or more road segments in common. The geographic information service provides information about transit routes, such as, for example, traffic speeds associated with traffic corresponding to traffic types on road segments and/or transit times associated with traffic corresponding to traffic types on road segments. Traffic condition information for road segments can be determined. The geographic information service can return traffic condition information to the requesting application.

As another example, in response to an API call that includes data indicative of a first location, a second location, and data indicative of a traffic type, the geographic information service selects a location from the first location to the first location based on traffic type. One or more transit routes to the two locations can be determined (eg, via a server computing system). For example, if the traffic type is HOV traffic, the geographic information service determines one or more transit routes such that each road segment in the transit route contains at least one traffic lane associated with the HOV traffic. and the traffic type is traffic for a particular type of vehicle, the geographic information service ensures that each road segment in the transit route contains at least one traffic lane associated with traffic for a particular type of vehicle. , one or more transit paths can be determined, and so on. The geographic information service, as described above, provides traffic condition information (e.g., one or more traffic speeds and/or one or multiple transit times) and return traffic information to the requesting application.

An automated process for route planning, e.g., for presenting as a suggestion to a user or for implementation in an autonomous vehicle, determining respective scores for each of a plurality of transit route candidates; and selecting transit path candidates based on their respective scores. Each transit route candidate may include one or more road segments each associated with traffic corresponding to a particular traffic type. For example, if a first transit path includes a first road segment, and the first road segment is associated with traffic corresponding to a first traffic type and a second traffic type, then the first transit path is (first A first candidate transit route (associated with traffic corresponding to one traffic type) and a second candidate transit route (associated with traffic corresponding to a second traffic type). A score for each transit route candidate may be determined using the corresponding traffic condition information for the traffic type, for example, using the traffic speed or transit time associated with the traffic type for the transit route candidate.

According to aspects of the present disclosure, the API can facilitate communication with a server computing system to obtain traffic condition information for transit areas. A server computing system obtains traffic sample data indicative of traffic (e.g., vehicle traffic, pedestrian traffic, other traffic, etc.) on one or more road segments within one or more transit areas. can be done. Traffic sample data may include at least the location of one or more objects (eg, vehicles, pedestrians, etc.) on one or more road segments at a first time and at a second time. A server computing system is associated with, for example, a person, a network of traffic sensors, and/or one or more objects from a plurality of objects (eg, a smartphone held by a person or in a vehicle)1 Traffic samples can be obtained from one or more data sources, such as observations provided by one or more mobile data sources. A server computing system determines a speed of travel associated with each of the plurality of objects based on the traffic sample data, and determines one or more traffic types (e.g., normal traffic) corresponding to the plurality of objects based on the speed of travel. , high-speed traffic, specific types of vehicle traffic, etc.). In some implementations, the server computing system may determine that one or more road segments are associated with one or more traffic types based on traffic sample data. For example, if the traffic sample data indicates that traffic on a road segment includes traffic corresponding to one or more traffic types, the server computing system determines that the road segment is associated with one or more traffic types. (eg, that a road segment includes one or more traffic lanes associated with one or more traffic types).

In some implementations, the server computing system may obtain traffic sample data indicative of traffic on the road segment, the traffic sample data indicative of speed of travel of one or more objects on the road segment. . A server computing system may determine one or more traffic speeds associated with the road segment based on the traffic sample data. A server computing system may determine one or more traffic speeds for each direction of traffic associated with a road segment.

By way of example, the server computing system may determine traffic on a road segment based on traffic sample data (e.g., average travel speeds associated with each of a plurality of objects on the road segment for each direction of traffic associated with the road segment). The average traffic speed of traffic can be determined.

As another example, the server computing system may determine distributions of multiple travel speeds associated with multiple objects on the road segment. A server computing system can determine the traffic speed for the road segment based on the overall peak of the distribution. Alternatively, the server computing system determines a first traffic speed for the road segment based on the first local peak of the distribution and determines the road segment speed based on the second local peak of the distribution. A second traffic speed for the can be determined. The server computing system determines a first local peak based on a first cluster of travel speeds in the distribution and a second local peak based on a second cluster of travel speeds in the distribution. can do. In this manner, the server computing system can determine multiple traffic speeds for a road segment based on multiple local peaks in the distribution.

The term "peak" may be defined according to peak definition criteria, such as predetermined peak definition criteria. The term "global peak" may refer to the peak whose distribution has the highest frequency value. A "local peak" can refer to a peak other than the global peak.

In one example, a clustering algorithm may be applied to multiple travel speeds to adaptively identify two (or more) clusters of travel speeds, each of which is identified as a respective peak. . The number of clusters can be identified based on clustering statistical significance criteria. The clustering algorithm may further identify a diffusion value for each cluster that indicates a respective range of velocities associated with each cluster, and a movement velocity is associated with one of the clusters if within the corresponding range. may be regarded as

Alternatively, the distribution is defined in terms of a respective percentage value for each of a plurality of consecutive speed ranges (e.g., non-overlapping speed ranges) that may span equal speed ranges, each percentage value representing the speed within the respective speed range. Denoting the percentage of moving objects, the peak definition criterion is that if the percentage value for a given velocity range is greater than the percentage value for the adjacent lower velocity range and the percentage value for the adjacent higher velocity range, then that velocity range is It can be the one that constitutes the peak.

In some implementations, the server computing system can obtain traffic sample data indicative of traffic on the road segment, the traffic sample data indicative of speed of travel of one or more objects on the road segment. . A server computing system may determine one or more traffic types associated with the road segment based on the traffic sample data. A server computing system may determine one or more traffic types for each direction of traffic associated with a road segment.

By way of example, the server computing system may determine one or more traffic speeds for road segments based on traffic sample data, as described above. If the server computing system determines a single traffic speed for a road segment, the server computing system determines that the single traffic speed is associated with traffic corresponding to a single traffic type and that the road segment is associated with a single traffic type (eg, a road segment includes one or more traffic lanes associated with a single traffic type, such as regular traffic). If the server computing system determines two or more traffic speeds for the road segment, the server computing system determines that the two or more traffic speeds are associated with traffic corresponding to the two or more traffic types; It can be determined that a road segment is associated with more than one traffic type (eg, a road segment includes one or more traffic lanes associated with more than one traffic type). In this manner, the server computing system can determine multiple traffic types associated with a road segment based on multiple traffic speeds for the road segment.

In some implementations, the server computing system may obtain traffic sample data indicative of traffic on the road segment, the traffic sample data including the speed of movement of one or more objects on the road segment and the traffic. Indicates type. A server computing system may determine one or more traffic types associated with the road segment based on the traffic sample data.

As an example, if the traffic sample data indicates traffic corresponding to high-speed traffic on a road segment, the server computing system determines that the road segment is associated with high-speed traffic (e.g., the road segment is associated with high-speed traffic1). (including one or more traffic lanes). As another example, if the traffic sample data indicates traffic corresponding to traffic for a certain type of vehicle, the server computing system may associate road segments with traffic for that type of vehicle (e.g., road segments may be associated with traffic for that type of vehicle). (including one or more traffic lanes associated with vehicle traffic). As another example, if the traffic sample data indicates traffic corresponding to multiple different traffic types on a road segment, the server computing system determines that the road segment is associated with multiple different traffic types (e.g., road segments have multiple traffic types). (including one or more traffic lanes associated with different traffic types).

In some implementations, the server-computing system can obtain data (eg, road segment attribute data) indicating one or more attributes associated with road segments in the transit area. The one or more attributes are, for example, the distance associated with a road segment, one or more traffic lanes in a road segment designated for traffic corresponding to one or more traffic types (for example, normal traffic , express traffic, and/or traffic lanes designated for certain types of vehicles). A server computing system can determine one or more traffic types associated with a road segment based on the road segment attribute data.

By way of example, the server computing system may determine a first traffic speed and a second traffic speed associated with traffic on the road segment based on traffic sample data indicative of traffic on the road segment, as described above. can be determined. If the road segment attribute data associated with the road segment indicates that the road segment includes one or more traffic lanes designated for normal traffic, the server computing system determines the first traffic speed and the first traffic speed. It can be determined that both of the two traffic speeds correspond to normal traffic and that the road segment is associated with normal traffic. Alternatively, if the road segment attribute data associated with the road segment includes at least one traffic lane designated for normal traffic and at least one traffic lane designated for express traffic , the server computing system determines that the first traffic speed corresponds to normal traffic and the second traffic speed corresponds to high speed traffic, and that the road segments are associated with normal traffic and high speed traffic. can decide.

In some implementations, a server computing system obtains traffic sample data indicative of traffic on a road segment, the traffic sample data indicative of movement of one or more objects on the road segment and traffic lanes, and 1 Road segment attribute data associated with a road segment indicative of one or more specified traffic lanes can be obtained. A server computing system may determine one or more traffic types corresponding to the traffic based on the traffic sample data and the road segment attribute data.

As an example, the road segment attribute data associated with the road segment indicates that the road segment includes the first traffic lane designated for HOV traffic, and the traffic sample data indicates that the traffic sample data is on the first traffic lane of the road segment. traffic, the server computing system may determine that the traffic on the first traffic lane corresponds to HOV traffic. The server computing system may determine an average travel speed of traffic on the first traffic lane to determine an average traffic speed of traffic corresponding to HOV traffic on the road segment. Alternatively, the road segment attribute data associated with the road segment indicates that the road segment includes multiple traffic lanes designated for HOV traffic, and the traffic sample data indicates that the road segment includes multiple traffic lanes designated for HOV traffic. When representing traffic, the server computing system can determine the average travel speed of traffic on multiple traffic lanes and determine the average traffic speed of traffic corresponding to HOV traffic on road segments.

According to aspects of the present disclosure, an application can request traffic condition information for transit areas via an API. In some implementations, an application may include a user interface (eg, a graphical user interface). A user can interact with the application through a user interface to request and obtain traffic condition information about the transit area.

As an example, a user can request traffic condition information for the first transit area from the application via the user interface. The application can send an API call to the server computing system that includes data indicating the first transit area (eg, an identifier associated with the first transit area). In response to the API call, the server computing system can determine map data indicating traffic condition information for the first transit area and provide the map data to the application through the API. An application can provide map data to a user via a user interface.

As another example, the user can request traffic condition information for the first transit area from the application via the user interface. In response to the request, the application can present a prompt to the user (eg, via a user interface) for traffic type, and the user can indicate the traffic type. For example, the user can indicate normal traffic for the traffic type if the user is traveling alone, or the user can indicate normal traffic for the traffic type if the user is traveling with one or more additional passengers. It can indicate fast traffic. Additionally or alternatively, the user can indicate certain types of vehicles for traffic types. The application can send an API call to the server computing system that includes data indicating the first transit area indicated by the user and the traffic type. In response to the API call, the server computing system determines map data indicative of traffic condition information associated with traffic corresponding to the indicated traffic type for the first transit area and provides the map data to the application through the API. can do. An application can provide map data to a user via a user interface.

As another example, the user can request traffic condition information for the first transit area from the application via the user interface. In response to the request, the application can prompt the user (eg, via the user interface) for the number of passengers. If the user is traveling alone, the user can indicate a single passenger. If the user travels with one or more additional occupants, the user can indicate two or more occupants for the number of occupants. The application can determine the traffic type corresponding to the number of passengers (e.g., single passenger instructions may correspond to normal traffic, and two or more passenger instructions may correspond to HOV traffic). may be used). The application can send an API call to the server computing system containing data indicating the first transit area and the determined traffic type. In response to the API call, the server computing system determines map data indicative of traffic condition information associated with traffic corresponding to the determined traffic type for the first transit area and provides the map data to the application through the API. can do. The application can provide map data to the user via a user interface.

In some implementations, in response to a user request for traffic condition information, the application can obtain user data indicating the traffic type associated with the request.

As an example, a user can request traffic condition information for a first transit area from an application via a user interface, and the user can specify the traffic type or number of passengers before being prompted for the information from the application. instructions can be included in the request. The application can send an API call to the server computing system that includes data indicating the transit area and traffic type indicated by the user. In response to the API call, the server computing system can determine map data indicating traffic condition information associated with the traffic type for the transit area and provide the map data to the application through the API. An application can provide map data to a user via a user interface.

As another example, the user can request traffic condition information for the first transit area from the application via the user interface. In response to the request, the application may obtain user data indicating the traffic type associated with the request for traffic condition information for the first transit area. User data may be, for example, whether the user prefers to see traffic condition information associated with normal traffic, prefers to see traffic condition information associated with HOV traffic, traffic condition information associated with toll lane traffic. It may include one or more preferences of the user, such as preference to view or preference to see traffic condition information associated with other traffic types.

As another example, the user can request traffic condition information for the first transit area from the application via the user interface. In response to the request, the application may obtain user data indicating the traffic type associated with the request for traffic condition information for the first transit area. User data may include user contextual information that applications can use to determine the traffic type associated with a request. For example, if an application obtains contextual information that includes the user's schedule, and based on the schedule determines that the request occurs at the same time as the user's daily solo commute, the application may can be determined to be for traffic condition information corresponding to traffic of If an application obtains contextual information, including the user's schedule, and determines, based on the schedule, that the request occurs at the same time as the user's daily carpool commute, then the application can determine if the request is for HOV transportation. It can be determined that it is for corresponding traffic situation information. If an application obtains contextual information that includes an appointment shared with one or more other users, and the application determines that the appointment's location includes the first transit area, the application may request the HOV It can be determined that it is for traffic condition information corresponding to traffic. An application can send an API call to a server computing system that includes data indicating a first transit area and a traffic type determined by the application. In response to the API call, the server computing system can determine map data indicative of traffic condition information associated with the traffic type for the first transit area and provide the map data to the application through the API. The application can provide map data to the user via a user interface. The use of schedules or appointments is given only as an example. Any type of contextual information indicating traffic type (e.g. location history, travel history/itinerary, purchase history (e.g. purchase of an electric vehicle that is allowed to travel in HOV traffic lanes), etc.) It will be appreciated that it can be used to determine the traffic type associated with a request for

In some implementations, in response to a user request for traffic condition information, the application determines the vehicle associated with the request (eg, the vehicle owned by the user, the vehicle the user is using at the time of the request, etc.). can do. The application can obtain vehicle data associated with the vehicle to determine the traffic type associated with the request.

As an example, a user can request traffic condition information for the first transit area from the application via the user interface. In response to the request, the application can obtain vehicle data indicating the specific type of vehicle associated with the request. Vehicle data includes vehicle make/model, vehicle weight, vehicle dimensions, vehicle type (e.g. truck, passenger car, etc.), vehicle engine type (e.g. electric, petrol, diesel, etc.), vehicle emissions data , or other information indicating the specific type of vehicle. An application may obtain vehicle data from one or more computing devices (eg, in-vehicle computing device, in-vehicle memory, etc.) associated with the vehicle. This may be via a direct interface with the vehicle's on-board system, or via a wireless interface (eg, Bluetooth®). If the application determines that vehicles of that specific type are required to travel only in traffic lanes designated for traffic corresponding to such specific type, then the application responds to user requests is associated with the traffic type corresponding to that particular type of vehicle. An application can send an API call to a server computing system that includes data indicating a first transit area and a traffic type determined by the application. In response to the API call, the server computing system can determine map data indicative of traffic condition information associated with the traffic type for the first transit area and provide the map data to the application through the API. An application can provide map data to a user via a user interface.

As another example, an application may obtain vehicle data indicating the number of passengers in the vehicle. Vehicle data may include the status of one or more seat or seat belt sensors in the vehicle. If the application determines that only a single seat or seat belt sensor is active, the application can determine that the vehicle contains a single occupant. If the application determines that more than one seat sensor or seat belt sensor is activated, the application must determine that the vehicle contains more than one occupant and the traffic type that the user request corresponds to HOV traffic. can be determined to be associated with An application can send an API call to a server computing system that includes data indicating a first transit area and a traffic type determined by the application. In response to the API call, the server computing system can determine map data indicative of traffic condition information associated with the traffic type for the first transit area and provide the map data to the application through the API. An application can provide map data to a user via a user interface.

As another example, an application may obtain ride data indicating toll payment devices in a ride. Ride data may include the state of the toll payment device (eg, active or inactive). If the application determines that the toll payment device is active, the application may determine that the user request is associated with a traffic type corresponding to toll lane traffic. An application can send an API call to a server computing system that includes data indicating a first transit area and a traffic type determined by the application. In response to the API call, the server computing system can determine map data indicative of traffic condition information associated with the traffic type for the first transit area and provide the map data to the application through the API. An application can provide map data to a user via a user interface.

As another example, an application may obtain vehicle data indicating the traffic lane in which the vehicle is located. Applications can, for example, obtain vehicle data from one or more front-facing cameras. The application determines whether the vehicle is in the leftmost lane, middle lane, rightmost lane, leftmost/rightmost, based on data obtained by one or more front-facing cameras. You can determine if you are in a certain number of lanes to the left/right from the current lane. An application may determine which traffic lane a vehicle occupies through application of one or more machine learning models (eg, neural networks) to camera data. An application can send an API call to a server computing system that includes data indicating a first transit area and traffic lane determined by the application. In response to the API call, the server computing system indicates traffic condition information associated with the traffic lane for the first transit area (eg, traffic condition information associated with traffic corresponding to the traffic type associated with the traffic lane). Map data can be determined and provided to applications through APIs. An application can provide map data to a user via a user interface.

The systems and methods described herein may provide several technical effects and advantages. For example, by enabling the server computing system to determine multiple traffic speeds associated with one or more traffic types for a transit area, the computing system can be used to simulate real-world physical systems (i.e., on roads). Useful data can be obtained that characterize the state of the object passing through. From this data, the server computer system can provide traffic condition information for transit areas corresponding to the user's traffic type. The client computing system sends a request for traffic condition information including an indication of the traffic type and responds to the indicated traffic type so that the client computing system can provide the user with more relevant traffic condition information. It can receive traffic information. In particular, the average traffic speed for a transit area can be misleading if the transit area is associated with multiple traffic types traveling in the same direction, for example by multiple traffic lanes. For example, the transit area may include congested normal traffic lanes and clear high speed traffic lanes. By determining multiple traffic speeds associated with one or more traffic types for a transit area, traffic condition information including multiple traffic speeds can be more reliable than average traffic speeds. Therefore, this information may enhance safety by providing users with more reliable and advanced information of traffic conditions they may encounter (eg at night).

Additionally, as noted above, the traffic condition information may be used by, for example, an automatic transit route suggestion module for proposing a transit route between a specified first location and a specified second location. It can be used for transit route planning. Improved route planning saves users time and can result in reduced fuel consumption and pollution. In one example, the present disclosure may provide methods and systems for controlling a self-driving vehicle that utilizes an automatic route suggestion module.

In addition to the above, the systems and methods described herein can determine traffic types applicable to a request for traffic condition information. For example, vehicle or user data may be obtained to determine the type of traffic condition information that applies to the request. This makes it possible to acquire more accurate traffic condition information.

Additionally, a computing system utilizing the systems and methods described herein can reduce the transmission of less relevant information, thereby reducing bandwidth requirements.

Exemplary embodiments of the present disclosure will now be discussed in greater detail with reference to the drawings.

FIG. 1 illustrates an exemplary computing environment according to exemplary embodiments of the present disclosure. Referring to FIG. 1, environment 100 includes client computing system 102, server computing system 106, and one or more networks 104 (e.g., one or more wired networks) that can interface with systems 102 and 106. and/or wireless networks).

System 102 includes one or more computing devices (e.g., computers (e.g., desktop computers, laptop computers, etc.), mobile computing devices (e.g., tablet computers, smartphones, etc.)) associated with a common (or same) user. etc.), wearable computing devices (eg, smart watches, etc.). The system 102 may be a navigation system embedded in the vehicle, which may be directly connected to (or form part of) the vehicle's internal computing system. System 102 may include one or more processors 108 , one or more sensors 110 , one or more communication interfaces 112 , and memory 114 .

Sensor 110 may determine location based on one or more computing devices (e.g., global positioning system (GPS) receivers) of system 102, signals received via communication interface 112, signal identifiers, signal strength, etc. data indicative of geographic location (e.g., circuitry configured to determine the number of passengers), data indicative of the number of occupants (e.g., seat sensors, seat belt sensors, etc.), and/or one or more computing devices of system 102 A component (eg, circuitry, etc.) configured to determine and/or receive data indicative of a traffic lane associated with (eg, a camera) may be included.

Communication interface 112 allows system 102 (eg, one or more computing devices of system 102) to communicate with one or more other computing devices in environment 100 (eg, system 106, one or more computing devices of system 106). including one or more interfaces (e.g., network interfaces, wired interfaces, wireless interfaces, etc.) configured to enable communication with (e.g., network 104, etc.) (e.g., computing devices, etc.) obtain.

Memory 114 may include instructions 116, which, when executed by processor 108, provide system 102 (eg, one or more computing devices of system 102) with one or more of the methods described herein. Multiple actions can be performed. For example, memory 114 may include one or more applications 118 (eg, application programs, etc.), application programming interfaces (APIs) 120 , user data 132 , and vehicle data 124 . User data 132 may include user preference information and/or contextual information indicating traffic types. Vehicle data 124 is data indicative of a vehicle associated with a user request for traffic condition information, such as, for example, make/model of vehicle, weight of vehicle, dimensions of vehicle, or other information indicative of a specific type of vehicle; It may include the status of one or more seat or seat belt sensors in the vehicle, the status of a toll payment device associated with the vehicle, and/or the traffic lane in which the vehicle is located.

According to embodiments of the present disclosure, API 120 may be configured to facilitate communication between application 118 and system 106 to obtain traffic condition information. In some embodiments, the application 118 accesses the user data 132 to determine the traffic type associated with a request for traffic condition information from the user in instances where the user consents to the use of such data; User preference information and/or contextual information can be retrieved. In some embodiments, application 118 may access vehicle data 134 to determine the traffic type associated with a request for traffic condition information from a user.

System 106 may be located remotely from system 102 (eg, may be located in a geographical location remote from the geographical location in which system 102 is located). System 106 may include one or more computing devices (eg, computers, servers, mainframes, virtual computing platforms, etc.). System 106 may include one or more processors 122 , one or more communication interfaces 124 , and memory 126 . Communication interface 124 allows system 106 (eg, one or more computing devices of system 106) to communicate with one or more other computing devices in environment 100 (eg, system 102, one or more computing devices of system 102). including one or more interfaces (e.g., network interfaces, wired interfaces, wireless interfaces, etc.) configured to enable communication with (e.g., network 104, etc.) (e.g., computing devices, etc.) obtain. Memory 126 may include instructions 128, which, when executed by processor 122, provide system 106 (eg, one or more computing devices of system 106) with one or more of the methods described herein. Multiple actions can be performed. Memory 126 may also include (eg, store, host, etc.) traffic sample data 130 indicative of traffic associated with a plurality of objects.

2A-2D illustrate exemplary event sequences according to exemplary embodiments of the present disclosure. Referring to FIG. 2A, at (208) a user 202 (eg, a user associated with system 102) executes one or more applications 118 (eg, on one or more computing devices of system 102). application) can request traffic information about the transit area. At 210, application 118 may make a call (eg, communicate data, etc.) using API 120 to request traffic condition information for the transit area. For example, an API call may be issued from application 118 to request traffic condition information from remote system 106 .

At (212), system 102 requests data from system 106 using API 120 (eg, via network 104, as indicated by the shaded box on the line extending downward from network 104). can communicate. For example, the request may be for traffic condition information for transit areas. System 106 may, for example, generate the requested data based on traffic sample data 130 (eg, based on data indicative of speed of movement of one or more objects on one or more road segments within the transit area). (or a portion thereof, etc.) can be determined, and at (214) the system 106 can communicate the requested data (such as a portion thereof) to the system 102 using the API 120, and the system 102 can may receive data requested from system 106 (such as a portion thereof). For example, the data may include map data showing traffic condition information for transit areas.

At (216), traffic condition information may be returned to application 118 (eg, the application that made the call at (202)) using API 120. FIG.

At 218, application 118 may provide traffic condition information to the user. For example, an application may display a map of a transit area and mark one or more road segments within the transit area with a color, shade, or other color corresponding to color-coded identifiers associated with the road segments contained in the map data. can be displayed using the visual properties of

In some implementations, the user 202 may include an indication of traffic type or number of passengers at 208 with a request for traffic condition information for the transit area from the application 118 . In this case, at (210), the application 118 may make a call (eg, communicate data, etc.) using the API 120 to request traffic condition information for the transit area associated with the traffic type. . An API call requesting traffic condition information may be received from application 118 . At (212), system 102 may communicate to system 106 a request for traffic condition information for the transit area associated with the traffic type. System 106 may determine the requested data, and at 214 system 106 may communicate the requested data to system 102 . At 216 , traffic condition information associated with the traffic type may be returned to application 118 using API 120 . At 218, application 118 may provide traffic condition information to the user.

Referring to FIG. 2B, at (208) a user 202 (eg, a user associated with system 102) executes one or more applications 118 (eg, on one or more computing devices of system 102). applications) can request traffic condition information about transit areas. At 220, the application 118 may present a prompt to the user for traffic type. User 202 can provide data to application 118 that indicates traffic type. For example, user 202 may select one or more traffic types from a predetermined list of traffic types via the user interface of application 118, and user 202 may indicate that the requested traffic condition information is in a single It can indicate whether it is for a passenger, or for multiple passengers, and/or the user 202 can indicate the specific type of vehicle associated with the request. Application 118 may determine the traffic type based on data provided by user 202 in response to the prompt. For example, if user 202 selects the first traffic type, application 118 may determine the traffic type as the first traffic type. As another example, if user 202 provides an indication of the number of passengers, application 118 can determine the traffic type corresponding to the number of passengers.

At 210, the application 118 may make a call (eg, communicate data, etc.) using the API 120 to request traffic condition information for the transit area associated with the traffic type. For example, an API call may be issued from application 118 to request traffic condition information from remote system 106 .

At (212), system 102 requests data from system 106 using API 120 (eg, via network 104, as indicated by the shaded box on the line extending downward from network 104). can communicate. For example, the request may be for traffic condition information for transit areas associated with a traffic type. System 106 may, for example, generate the requested data based on traffic sample data 130 (eg, based on data indicative of speed of movement of one or more objects on one or more road segments within the transit area). (or a portion thereof, etc.) can be determined, and at (214) the system 106 can communicate the requested data (such as a portion thereof) to the system 102 using the API 120, and the system 120 can may receive data requested from system 106 (such as a portion thereof). For example, the data may include map data showing traffic condition information for transit areas associated with traffic types.

At (216), traffic condition information may be returned to application 118 (eg, the application that made the call at (202)) using API 120. FIG.

At 218, application 118 may provide traffic condition information to the user. For example, an application may display a map of a transit area and mark one or more road segments within the transit area with a color, shade, or other color corresponding to color-coded identifiers associated with the road segments contained in the map data. can be displayed using the visual properties of

Referring to FIG. 2C, at (208) user 202 (eg, a user associated with system 102) passes from application 118 (eg, an application running on one or more computing devices of system 102). You can request traffic information for your area. At (224), application 118 may access user data 132 in memory 114 to determine the traffic type corresponding to the request for traffic condition information for the transit area. At 226 , application 118 may retrieve data from user data 132 indicating traffic type.

Referring to FIG. 2D, at (208) user 202 (eg, a user associated with system 102) passes from application 118 (eg, an application running on one or more computing devices of system 102). You can request traffic information for your area. At (228), application 118 may access vehicle data 134 in memory 114 to determine the traffic type corresponding to the request for traffic condition information for the transit area. At 230 , application 118 may retrieve data indicating traffic type from vehicle data 134 .

3A-3C illustrate visualizations of traffic condition information according to exemplary embodiments of the present disclosure. Referring to FIG. 3A, there is a transit path 302 from location A to location B and a transit path 304 from location B to location A. FIG. Each transit path 302 and 304 may include multiple transit areas 311 , 312 , 313 , 314 , 315 , 316 , and 317 . Each of transit areas 311, 312, 313, 314, 315, 316, and 317 may include one or more road segments. For example, transit area 311 includes road segments 331 and 341, transit area 312 includes road segments 332 and 342, transit area 313 includes road segments 333 and 343, transit area 314 includes road segments 334 and 344, Passage area 315 includes road segments 335 and 345 and passage area 316 includes road segments 336 and 346 .

According to an exemplary embodiment of the present disclosure, transit route 302 may be associated with a first traffic speed corresponding to a first traffic type and a second traffic speed corresponding to a second traffic type. For example, a first traffic speed may be greater than the speed limit associated with transit route 302 and a second traffic speed may be less than the speed limit associated with transit route 302 .

As shown in FIG. 3B, when the user requests traffic condition information for transit route 302 associated with the first traffic type, system 106 indicates the first traffic speed associated with the first traffic type. Map data can be determined. Map data indicative of the first traffic speed may include a first color-coded identifier (shown in light gray) associated with each road segment of transit route 302 .

As shown in FIG. 3C, if the user request requests traffic condition information about transit route 302 associated with a second traffic type, system 106 selects a second traffic speed associated with the second traffic type. Map data to be shown can be determined. Map data indicative of the second traffic speed may include a second color-coded identifier (shown in dark gray) associated with each road segment of transit route 302 .

4A-4B illustrate example distributions of travel speeds on road segments, according to example embodiments of the present disclosure. The distribution of travel speeds on the road segment may be based on traffic sample data 130 indicating multiple travel speeds associated with multiple objects (eg, vehicles, pedestrians, etc.) on the road segment. The system 106 may include, for example, observations provided by a person, a network of traffic sensors, and/or one or more mobile data sources associated with one or more objects from a plurality of objects (e.g., The traffic sample data 130 can be obtained from one or more data sources, such as a smart phone in a vehicle or in a vehicle. The traffic sample data 130 may include at least the positions of a plurality of objects on the road segment at a first time and at a second time. The system 106 can determine travel speeds associated with each of the plurality of objects based on the traffic sample data. Alternatively, system 106 may obtain traffic sample data 130 that includes multiple travel speeds associated with multiple objects.

As shown in FIG. 4A, the distribution of travel speeds on the first road segment may contain a single overall peak, and the geographic information service may, based on that distribution, determine the speed of the first road segment. can be determined to be associated with a single traffic speed. A geographic information service may associate a traffic type with a single traffic speed (eg, normal traffic) and a road segment with a traffic type.

As shown in FIG. 4B, the distribution of travel speeds on the first road segment may include a first local peak and a second local peak. The geographic information service associates the first road segment with a first traffic speed corresponding to a first local peak and a second traffic speed corresponding to a second local peak based on the distribution. can be determined to be The geographic information service may associate a first traffic type with a first traffic speed and a second traffic type with a second traffic speed.

FIG. 5 shows a flow diagram of a method 500 for determining traffic condition information, according to an exemplary embodiment of the present disclosure. At 501, method 500 may include obtaining traffic sample data associated with a first direction of traffic on a first road segment. For example, system 106 may obtain traffic sample data 130 associated with a first direction of traffic on a first road segment. Traffic sample data 130 may include data indicative of multiple travel speeds associated with multiple objects.

At (502), method 500 may include determining a plurality of average traffic speeds for a first direction of traffic. For example, the system 106 may determine a plurality of average traffic speeds for a first direction of traffic on the first road segment based at least in part on the plurality of travel speeds in the traffic sample data 130. . Each of the plurality of average traffic speeds may be associated with one or more lanes of the first road segment. Specifically, the system 106 can determine a plurality of travel speed distributions and identify a plurality of peaks based on the plurality of travel speed distributions. Each peak from the multiple peaks may be associated with multiple subsets of travel velocities. The system 106 identifies a first peak from the plurality of peaks based at least in part on a first cluster of travel speeds distributed about the first peak, and a second peak from the plurality of peaks. may be determined based at least in part on a second cluster of a plurality of travel speeds distributed around a second peak. A subset of the plurality of travel speeds associated with the first peak may correspond to the first cluster, and a subset of the plurality of travel speeds associated with the second peak may correspond to the second cluster. The system 106 may determine an average traffic speed for each peak from multiple peaks based at least in part on the average of a subset of travel speeds associated with the peak. The system 106 may associate average traffic speeds for each peak from multiple peaks with different traffic types from multiple traffic types.

At 503, method 500 may include associating multiple average traffic speeds with multiple average traffic types. For example, the system 106 can associate each of multiple average traffic speeds with at least one of multiple traffic types. Specifically, the system 106 calculates an average traffic speed from a plurality of average traffic speeds, a traffic type from a plurality of traffic types, and its average traffic speed relative to the plurality of average traffic speeds. The association can be based at least in part on the velocity value. The system 106 associates the average traffic speed with the lowest value among the plurality of average traffic speeds with a first traffic type from the plurality of traffic types, and associates the average traffic speed with the highest value among the plurality of average traffic speeds. It can be associated with a second traffic type from multiple traffic types.

At 504, method 500 may include determining map data based on multiple traffic types and associated average traffic speeds. For example, the system 106 may determine map data based at least in part on multiple traffic types and associated average traffic speeds.

At 505, method 500 may include transmitting map data. For example, system 106 can transmit map data corresponding to at least one of a plurality of traffic types to system 102 in response to the request. Specifically, the system 106 provides a first routing option corresponding to a first average speed associated with a first traffic type and a second routing option corresponding to a second average speed associated with a second traffic type. Multiple routing or navigation options may be sent, including at least two routing options. In some implementations, the request may include the first traffic type and the map data may correspond to the first traffic type. The map data may correspond to two or more of the multiple traffic types, and the map data may include a comparison of a first traffic type and at least a second traffic type from the multiple traffic types. In some implementations, the request is a routing request and the map data sent includes first routing data based on the first average speed and second routing data based on the second average speed. can contain.

FIG. 6 illustrates an example flow diagram of a method 600 for associating multiple traffic speeds with a traffic type, according to an example embodiment of the present disclosure. At 601, method 600 may include determining a distribution of a plurality of travel speeds. For example, system 106 may determine distributions of multiple travel speeds based on traffic sample data 130 .

At 602, method 600 may include identifying a plurality of peaks based on the distribution. For example, the system 106 can identify multiple peaks based on multiple travel velocity distributions. Each peak from the multiple peaks may be associated with multiple subsets of travel velocities. The system 106 identifies a first peak from the plurality of peaks based at least in part on a first cluster of travel speeds distributed about the first peak, and a second peak from the plurality of peaks. may be determined based at least in part on a second cluster of a plurality of travel speeds distributed around the second peak. A subset of the plurality of travel speeds associated with the first peak may correspond to the first cluster, and a subset of the plurality of travel speeds associated with the second peak may correspond to the second cluster.

At 603, the method 600 may include determining an average traffic speed for each peak based on travel speeds associated with the peak. For example, the system 106 may determine an average traffic speed for each peak from multiple peaks based at least in part on the average of a subset of travel speeds associated with the peak.

At 604, the method 600 may include associating the average traffic speed for each peak with a traffic type. For example, the system 106 may associate average traffic speeds for each peak from multiple peaks with different traffic types from multiple traffic types.

FIG. 7 shows an example flow diagram of a method 700 for determining traffic condition information, according to an example embodiment of this disclosure. At 701, method 700 may include receiving a request for traffic condition information. For example, application 118 may receive one or more requests for traffic condition information from user 202 . One or more requests from user 202 may include data indicating a first location, a second location, and a traffic type. Applications can provide requests to system 106 via API 120 .

At 702, method 700 may include determining a first transit path. For example, system 106 can determine a first transit path from a first location to a second location. The first transit route may include one or more transit regions associated with a first traffic type from multiple traffic types.

At 703, the method 700 may include determining one or more transit times corresponding to one or more traffic types associated with the first transit route. For example, system 106 may identify a first transit region of a first transit route associated with more than one traffic type from multiple traffic types. The two or more traffic types may include a first traffic type and a second traffic type from multiple traffic types. System 106 may determine a first transit duration for the first transit route corresponding to a traffic speed associated with the first traffic type. Specifically, system 106 may determine the traffic speed for each of the one or more transit areas based at least in part on the average traffic speed associated with the first traffic type for the transit area. System 106 may determine a first transit duration for the first transit route based at least in part on the average traffic speed for each of the one or more transit regions. In some implementations, the system 106 may determine a second transit duration for the first transit route corresponding to traffic speeds associated with a second traffic type from multiple traffic types.

At 704, method 700 may include determining map data based on the traffic type associated with the request. For example, the system 106 associates a first traffic type with the user 202 based at least in part on data indicative of the traffic type received from the user 202 and indicates a first transit time for the first transit route. Map data can be determined. Specifically, the system 106 obtains data indicative of speed limits for each of the one or more transit areas, associates a color-coded identifier for each of the one or more transit areas based on the difference, Map data may be determined based on color-coded identifiers associated with each of the one or more transit areas. In some implementations, the system 106 may determine map data indicating a second transit duration for the first transit route if the second transit duration is less than the first transit duration. .

At 705, method 700 may include transmitting map data. For example, system 106 may provide map data to application 118 via API 120 in response to a request for traffic condition information.

FIG. 8 shows an example flow diagram of a method 800 for determining traffic condition information, according to an example embodiment of this disclosure. At 801, method 800 may include receiving a request for traffic condition information. For example, application 118 may receive one or more requests for traffic condition information from user 202 . One or more requests from user 202 may include data indicating a first location, a second location, and a traffic type. Applications can provide requests to system 106 via API 120 . In some implementations, the system 106 may provide a prompt to the user 202 to select a traffic type and receive data from the user 202 indicating the traffic type in response to the prompt.

At 802, method 800 may include determining a first transit route associated with a first traffic type and a second transit route associated with a second traffic type. For example, system 106 can determine a first transit path from a first location to a second location. The first transit route may include one or more transit regions associated with a first traffic type from multiple traffic types. System 106 can also determine a second transit path from the first location to the second location. The second transit route may include at least one transit region associated with the second traffic type from the plurality of traffic types. In some implementations, both the first transit path and the second transit path may include a first transit region associated with more than one traffic type from multiple traffic types. Two or more traffic types include a first traffic type and a second traffic type.

At (803), method 800 may include determining a first transit duration corresponding to a first traffic type and a second transit duration corresponding to a second traffic type. For example, system 106 may determine a first transit duration for a first transit route corresponding to a traffic speed associated with a first traffic type. System 106 may also determine a second transit duration for the second transit route corresponding to a traffic speed associated with the second traffic type.

At 804, the method 800 may include determining map data based on the first and second transit durations. For example, system 106 may associate a first traffic type from multiple traffic types with user 202 based at least in part on the first transit duration and the second transit duration. Specifically, system 106 may associate the first traffic type with user 202 if the first transit duration is shorter than the second transit duration. Alternatively, system 106 may associate a second traffic type from multiple traffic types with user 202 if the second transit duration is less than the first transit duration.

At 805, method 800 may include transmitting map data. For example, system 106 may provide map data to application 118 via API 120 in response to a request for traffic condition information.

FIG. 9 shows an example flow diagram of a method 900 for displaying traffic condition information, according to an example embodiment of this disclosure. At 901, the method 900 may include requesting traffic condition information. For example, application 118 may receive a request for traffic condition information from user 202 . The request may include data indicating one or more road segments (eg, transit routes, transit areas, etc.). In some implementations, the request may include a traffic type associated with the request provided by the user (eg, data indicating selected traffic type, number of passengers, type of vehicle, etc.).

At 902, method 900 may include determining a traffic type associated with the request if the request does not include data indicating the traffic type. For example, in some implementations, application 118 may provide user 202 with prompts to select a traffic type, number of passengers, and/or a type of vehicle. Application 118 may receive data indicating traffic type from user 202 in response to the prompt. In some implementations, application 118 uses user data 132 and/or vehicle data 134 to determine the traffic type associated with the request (e.g., from a computing system such as sensors and memory embedded in the vehicle). can be taken out. User data 132 may include one or more preferences associated with user 202 and/or contextual information associated with user 202 . Vehicle data 134 includes vehicle make/model, vehicle weight, vehicle dimensions, vehicle type (eg, truck, passenger car, etc.), vehicle engine type (eg, electric, petrol, diesel, etc.), vehicle emissions. data or other information indicating the particular type of vehicle associated with the request, the status of one or more seat or seat belt sensors in the vehicle, the status of the toll payment device, and/or the traffic in which the vehicle is located; May include data indicating lanes. Application 118 may determine the traffic type associated with the request based on user data 132 and/or vehicle data 134 . In some implementations, application 118 may provide user data 132 and/or vehicle data 134 (or portions thereof) to system 106 via API 120 to determine the traffic type associated with the request. can. For example, application 118 can provide data indicative of vehicle traffic lanes to system 106 via API 120, and system 106 can determine traffic lanes based on road segment attribute data indicative of traffic types associated with the traffic lanes. A traffic type associated with a can be determined.

At 903, the method 900 may include determining map data based on the traffic type associated with the request. For example, application 118 may request traffic condition information for a road segment from system 106 via API 120 . Application 118 may provide data to system 106 indicating the determined traffic type associated with the request. In some implementations, application 118 may provide user data 132 and/or vehicle data 134 (or portions thereof) to system 106 via API 120, as described above. The system 106 determines map data indicating traffic condition information for the road segment corresponding to the traffic type associated with the request (eg, traffic speeds and/or transit times associated with traffic corresponding to the traffic type on the road segment). can do. The map data may include color-coded identifiers associated with each road segment from multiple road segments. System 106 can provide the determined map data to application 118 .

At 904, the method 900 may include displaying map data. For example, application 118 may display a graphical user interface that includes a map of road segments. Segments may be displayed based on a color-coded identifier associated with each road segment from multiple road segments.

The techniques discussed herein are based on servers, databases, software applications, and/or other computer-based systems, as well as actions taken and information transmitted to and/or from such systems. to mention. The inherent flexibility of computer-based systems allows for a wide variety of possible configurations, combinations, and/or partitioning of tasks and/or functions among components. For example, the processes discussed herein can be implemented using a single device or component and/or using multiple devices or components operating in combination. The database and/or application may be implemented in a single system and/or distributed across multiple systems. Distributed components can operate serially and/or in parallel.

Various connections between elements are discussed in the description above. These connections are conventional and may be direct and/or indirect, wired and/or wireless, unless specified otherwise. In this regard, the specification is not intended to be limiting.

The steps shown and/or described are for illustrative purposes only and may be omitted, combined and/or performed in a different order than shown and/or described. The number of steps shown is for ease of reference only and does not imply that any particular order is required or preferred. The functions and/or steps described herein may be performed by one or more computers and/or other devices to perform one or more functions described herein. It can be embodied in usable data and/or computer-executable instructions. Generally, such data and/or instructions perform particular tasks and/or are of particular data types when executed by one or more processors in computers and/or other data processing devices. implements, including routines, programs, objects, components, data structures, etc. Computer-executable instructions may be stored on computer-readable media such as hard disks, optical disks, removable storage media, solid-state memory, read-only memory (RAM), and the like. It will be appreciated that the functionality of such instructions may be combined and/or distributed as desired. Additionally, functionality may be embodied in whole or in part in firmware and/or hardware equivalents such as integrated circuits, application specific integrated circuits (ASICs), field programmable gate arrays (FPGAs), and the like. Certain data structures may be used to more effectively implement one or more aspects of the present disclosure, and such data structures may be computer-executable instructions and/or instructions described herein. or within computer usable data.

Although not required, it is appreciated that the various aspects described herein can be embodied as methods, systems, apparatus, and/or one or more computer-readable media storing computer-executable instructions. Traders will understand. Accordingly, aspects can be described as wholly hardware embodiments, wholly software embodiments, wholly firmware embodiments, and/or embodiments which combine software, hardware, and/or firmware aspects in any combination. can take the form of

Various methods and activities may be effective across one or more computing devices and/or networks, as described herein. The functionality may be distributed in any manner or may be located in a single computing device (eg, server, client computer, user device, etc.).

Aspects of the present disclosure have been described in terms of illustrative embodiments thereof. Numerous other embodiments, modifications and/or variations within the scope and spirit of the appended claims may occur to those skilled in the art from a review of this disclosure. For example, the steps illustrated and/or described may be performed out of the order recited and/or one or more illustrated steps may be optional and/or Those skilled in the art can understand that they may be combined. Any and all features in the following claims may be combined and/or permuted in any possible way. Although the present subject matter has been described in detail in terms of various specific exemplary embodiments thereof, each example is provided by way of explanation rather than limitation of the disclosure. Modifications, variations and/or equivalents of such embodiments can be readily devised by those of ordinary skill in the art upon reaching the foregoing understanding. Accordingly, the subject disclosure does not exclude the inclusion of such modifications, variations and/or additions of the subject matter, as would be readily apparent to those skilled in the art. For example, features illustrated and/or described as part of one embodiment can be used with another embodiment to yield a still further embodiment. Accordingly, this disclosure is intended to embrace such modifications, variations and/or equivalents.

In addition to the above description, it should be noted that the systems, applications, or features described herein may use user information (e.g., user preferences, user location, contextual information about the user's social networks, social behavior, activities, or occupation), and whether the user is sent content or communications from the server based on the user information; A user may be provided with controls that allow the Additionally, certain data may be treated in one or more ways before being stored or used such that personally identifiable information is removed. For example, a user's identity may be used in such a way that personally identifiable information about the user cannot be determined, or the geographic location of the user whose location information is obtained such that the user's specific location cannot be determined (e.g., may be treated as generalizable (to the city, zip code, or state level). Thus, users have control over what information is collected about them, how that information is used, and what information is provided to them.

102 Client Computing System
104 network
106 server computing system
108 processors
110 sensors
112 communication interface
114 memory
116 instructions
118 applications
120 APIs
122 processors
124 communication interface
126 memories
128 instructions
130 traffic sample data
132 User data
134 vehicle data
302 Passage
304 Passage
311 transit area
312 pass area
313 Passage area
314 pass area
315 pass area
316 pass area
317 transit area
331 road segments
332 road segments
333 road segments
334 road segments
335 road segments
336 road segments
341 road segments
342 road segments
343 road segments
344 road segments
345 road segments
346 road segments

Claims (30)

A computer-implemented method for determining traffic conditions, comprising:
obtaining, by one or more computing devices, traffic sample data associated with a first direction of traffic on a first road segment, the traffic sample data associated with a plurality of objects; a step containing data indicative of the speed of movement of the
determining, by the one or more computing devices, a plurality of average traffic speeds for the first direction of traffic on the first road segment based on the plurality of travel speeds;
associating, by the one or more computing devices, each of the plurality of average traffic speeds with at least one of a plurality of traffic types;
determining, by the one or more computing devices, map data based on the plurality of traffic types and associated average traffic speeds;
sending, by the one or more computing devices, map data corresponding to at least one of the plurality of traffic types to a client device in response to a request;
A computer-implemented method. determining the plurality of average traffic speeds for the first direction of traffic on the first road segment based on the plurality of travel speeds;
determining, by the one or more computing devices, a distribution of the plurality of movement speeds;
identifying, by the one or more computing devices, a plurality of peaks based on the distribution of the plurality of travel speeds, wherein each peak from the plurality of peaks is a subset of the plurality of travel speeds; a step associated with
determining, by said one or more computing devices, an average traffic speed for each peak from said plurality of peaks based on an average of said subset of travel speeds associated with said peak;
The computer-implemented method of claim 1. identifying the plurality of peaks based on the distribution of the plurality of travel speeds, wherein each peak from the plurality of peaks is associated with a subset of the plurality of travel speeds;
identifying, by the one or more computing devices, the first peak from the plurality of peaks based on a first cluster of the plurality of travel speeds distributed around the first peak; , said subset of said plurality of travel velocities is associated with said first peak corresponding to said first cluster;
identifying, by the one or more computing devices, the second peak from the plurality of peaks based on a second cluster of the plurality of travel speeds distributed around the second peak; , wherein said subset of said plurality of travel velocities is associated with said second peak corresponding to said second cluster;
3. The computer-implemented method of claim 2. further comprising, by the one or more computing devices, associating the average traffic speed for each peak from the plurality of peaks with a different traffic type from the plurality of traffic types;
3. The computer-implemented method of claim 2. associating each of the plurality of average traffic speeds with at least one of a plurality of traffic types;
The one or more computing devices calculate an average traffic speed from the plurality of average traffic speeds for the plurality of traffic types based on the value of the average traffic speed relative to the plurality of average traffic speeds. including associating with a traffic type from
The computer-implemented method of claim 1. associating each of the plurality of average traffic speeds with at least one of the plurality of traffic types;
associating, by the one or more computing devices, the lowest value average traffic speed among the plurality of average traffic speeds with a first traffic type from the plurality of traffic types;
and associating, by said one or more computing devices, a highest valued average traffic speed among said plurality of average traffic speeds with a second traffic type from said plurality of traffic types;
The computer-implemented method of claim 1. The traffic sample data includes data indicative of traffic types associated with the plurality of objects, and based on the plurality of speeds of travel associated with the plurality of objects, the first traffic on the first road segment is determined based on the plurality of travel speeds associated with the plurality of objects. determining the plurality of average traffic speeds for the direction of
determining, by the one or more computing devices, a first set of objects and a second set of objects from the plurality of objects, wherein each object in the first set associated with one traffic type, wherein each object in said second set is associated with a second traffic type;
a first average traffic speed based on travel speeds associated with each object in the first set of objects by the one or more computing devices; and each object in the second set of objects. and a second average traffic speed based on the associated travel speed.
The computer-implemented method of claim 1. associating each of the plurality of average traffic speeds with at least one of a plurality of traffic types;
associating, by the one or more computing devices, the first average traffic speed with the first traffic type and associating the second average traffic speed with the second traffic type;
8. The computer-implemented method of claim 7. each of the plurality of average traffic speeds is associated with one or more lanes of the first road segment;
The computer-implemented method of claim 1. transmitting the map data corresponding to at least one of the plurality of traffic types;
A first routing option corresponding to a first average speed associated with a first traffic type and a second average speed associated with a second traffic type by the one or more computing devices sending a plurality of routing or navigation options, including at least a second routing option;
The computer-implemented method of claim 1. the request includes a first traffic type;
the map data corresponds to the first traffic type;
The computer-implemented method of claim 1. the map data corresponding to two or more of the plurality of traffic types;
the map data includes a comparison between the first traffic type and at least a second traffic type from the plurality of traffic types;
12. The computer-implemented method of claim 11. the request is a routing request;
wherein the transmitted map data includes first routing data based on a first average speed and second routing data based on a second average speed;
The computer-implemented method of claim 1. A computer-implemented method for determining traffic conditions, comprising:
receiving, by one or more computing devices, one or more requests for traffic condition information from a user, the one or more requests being at a first location, a second location, and a step including data indicative of a traffic type;
determining, by the one or more computing devices, a first transit route from the first location to the second location, wherein the first transit route is selected from a plurality of traffic types; including one or more transit areas associated with the first traffic type of
determining, by the one or more computing devices, map data indicative of a first transit time for the first transit route, wherein the first transit time corresponds to the first transit time; a step corresponding to the traffic speed associated with the type;
providing, by the one or more computing devices, the map data to the user in response to the request for the traffic condition information;
A computer-implemented method. determining said map data indicative of said first transit duration for said first transit route, said first transit duration corresponding to said traffic speed associated with said first traffic type; do, the step is
identifying, by the one or more computing devices, a first transit region of the first transit route associated with two or more traffic types from the plurality of traffic types, wherein the two wherein said traffic types include said first traffic type and a second traffic type from said plurality of traffic types;
associating, by the one or more computing devices, the first traffic type with the user based on the data received from the user indicating the traffic type;
15. The computer-implemented method of claim 14. determining, by said one or more computing devices, a second transit duration for said first transit route, said second transit duration being associated with said second traffic type; a step corresponding to traffic speed;
and providing, by the one or more computing devices, data indicative of the second transit duration to the user if the second transit duration is less than the first transit duration. include,
16. The computer-implemented method of claim 15. determining said map data indicative of said first transit duration for said first transit route, said first transit duration corresponding to said traffic speed associated with said first traffic type; do, the step is
determining, by said one or more computing devices, at least a second transit route from said first location to said second location, said second transit route comprising said plurality of traffic routes; including at least one transit area associated with a second traffic type from the type;
associating, by the one or more computing devices, the first traffic type from the plurality of traffic types with the user based on the first transit duration and the second transit duration; and wherein said second transit time corresponds to a traffic speed associated with said second traffic type;
15. The computer-implemented method of claim 14. both the first transit route and the second transit route include a first transit area associated with two or more traffic types from the plurality of traffic types;
said two or more traffic types include said first traffic type and said second traffic type;
18. The computer-implemented method of claim 17. said first traffic type is associated with said user if said first transit time is less than said second transit time;
18. The computer-implemented method of claim 17. the first location is a first geographic location;
said second location is a second geographic location,
15. The computer-implemented method of claim 14. wherein the plurality of traffic types includes at least one traffic type corresponding to vehicle traffic with a specified number of passengers or more and at least one traffic type corresponding to other traffic;
15. The computer-implemented method of claim 14. receiving from the user the data indicative of the traffic type;
said one wherein said one or more computing devices associate said first transit route from said first location to said second location with at least said first traffic type and said second traffic type; or in response to determining to include multiple transit areas, providing a prompt to the user for the user to select a traffic type;
receiving by the one or more computing devices from the user the data indicative of the traffic type from the user responding to the prompt;
15. The computer-implemented method of claim 14. determining said map data indicative of said first transit duration for said first transit route, said first transit duration corresponding to said traffic speed associated with said first traffic type; do, the step is
determining, by said one or more computing devices, a traffic speed for each of said one or more transit areas, wherein said traffic speed for each transit area is equal to said first traffic velocity for said transit area; a step based on the average traffic speed associated with the type;
determining, by the one or more computing devices, the first transit duration for the first transit route based on the average traffic speed for each of the one or more transit regions; include,
15. The computer-implemented method of claim 14. obtaining, by said one or more computing devices, data indicative of a speed limit for each of said one or more transit areas;
determining, by the one or more computing devices, the difference between the speed limit and the traffic speed for each of the one or more transit areas;
associating, by the one or more computing devices, a color-coded identifier for each of the one or more transit areas based on the difference;
determining, by the one or more computing devices, the map data based on the color-coded identifiers associated with each of the one or more transit areas;
24. The computer-implemented method of claim 23. The color-coded identifiers for transit areas are
corresponding to a first color if the traffic speed is lower than the speed limit for the passage area by at least a first threshold amount;
corresponding to a second color if the traffic speed is lower than the speed limit for the passage area by a second threshold amount that is less than the first threshold amount;
Corresponding to a third color if the traffic speed is less than the speed limit for the passage area by an amount less than the second threshold amount or if the traffic speed is greater than or equal to the speed limit for the passage area ,
25. The computer-implemented method of claim 24. one or more processors;
a computer readable medium having instructions stored thereon for performing the following actions by the one or more processors:
A computing system, wherein the operation includes:

receiving one or more requests for transit information from a user, the one or more requests including data indicative of a first location, a second location, and a traffic type;
determining a first transit route from said first location to said second location, wherein said first transit route is one associated with a first traffic type from a plurality of traffic types; or comprising a plurality of transit areas; and
identifying a first transit area from the one or more transit areas, wherein the first transit area is associated with two or more traffic types from the plurality of traffic types; wherein said traffic types include said first traffic type and a second traffic type from said plurality of traffic types;
determining a first transit duration and a second transit duration for said first transit route, wherein said first transit duration corresponds to a traffic speed associated with said first traffic type; , said second transit time corresponds to a traffic speed associated with said second traffic type;
Based on said first transit duration, said second transit duration, and said data indicative of said traffic type received from said user, determining said first traffic type or said second traffic type to said user. a step of associating with
providing map data to the user in response to the request for transit information, the map data corresponding to the traffic type associated with the user;
computing system. A computer-implemented method for determining traffic conditions, comprising:
receiving, by one or more computing devices, a request for traffic condition information from a user, said request including data indicative of a first location, a second location, and a first traffic type; , step and
determining, by said one or more computing devices, one or more transit routes from said first location to said second location, each transit route corresponding to said first traffic type; a step including one or more road segments associated with
determining, by the one or more computing devices, traffic condition information associated with traffic corresponding to the first traffic type for each of the one or more transit routes;
determining, by said one or more computing devices, map data indicative of traffic condition information associated with traffic corresponding to said first traffic type for at least one of said one or more transit routes; When,
providing, by the one or more computing devices, the map data to the user in response to the request for traffic condition information;
A computer-implemented method. A computer-implemented method for determining traffic conditions, comprising:
receiving, by one or more computing devices, a request for traffic condition information from a user, said request including data indicative of one or more road segments;
obtaining, by the one or more computing devices, at least one of user data or vehicle data indicative of a traffic type associated with the request for traffic condition information;
determining, by the one or more computing devices, map data including traffic condition information associated with traffic corresponding to the traffic type for the one or more road segments, the map data comprising: determined based on said user data or vehicle data indicative of said traffic type associated with said request for traffic condition information;
providing, by the one or more computing devices, the map data to the user in response to the request for traffic condition information;
A computer-implemented method. said user data includes at least one of one or more travel preferences associated with said user or contextual information associated with said user;
29. The computer-implemented method of claim 28. The vehicle data may include vehicle type, vehicle model, vehicle weight, vehicle dimensions, vehicle specific type, one or more seat or seat belt sensor status, toll payment device status, or traffic lane. including at least one of
29. The computer-implemented method of claim 28.

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